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<h2>About us</h2>

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PeakWhiz a user-friendly, comprehensive framework that allows users to conduct sophisticated integrative analysis of ChIP-seq data.
Running on a web-based platform, PeakWhiz eliminates the problems associated with platform discrepancies and data management. 
<br><br>
In terms of functionality, PeakWhiz endorses the full range of analyses starting from read mapping to peak calling and subsequent functional analysis. 
By providing support for each stage of processing, data transfer from one analysis to the next is seamless and efficient, requiring little user specified details to derive biologically meaningful results. 
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PeakWhiz takes the ease of data transfer to a whole new level with the integration with Illumina <a href='https://basespace.illumina.com/home/index'>BaseSpace</a> which is directly integrated with Illumina sequencing platforms to automatically retrieve results from sequencing runs. 
Alternatively, users can upload their own data sets in a variety of formats to be analyzed 'on-the- fly' in a matter of clicks. 
Taken together, PeakWhiz aims to automate and streamline the ChIP-seq analysis pipeline like never before in an attempt to understand the complex mechanisms by which transcription factors and other epigenetic factors work. 
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<h2><strong>PeakWhiz ChIP-seq Pipeline:</strong></h2>
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<strong>Pre-processing:</strong><br>
1) Read Mapping with <a href='http://www.ncbi.nlm.nih.gov/pubmed/?term=Fast+gapped-read+alignment+with+Bowtie+2'>Bowtie2</a><br>
2) Peak Calling with <a href='http://www.ncbi.nlm.nih.gov/pubmed/18798982'>MACS</a><br>
<br>
<strong>Integrative Analysis:</strong><br>
1) De Novo Motif Analysis with <a href='http://www.ncbi.nlm.nih.gov/pubmed/?term=Simultaneously+learning+DNA+motif+along+with+its+position+and+sequence+rank+preferences+through+EM+algorithm'>SEME</a><br>
2) Motif Enrichment Analysis with <a href='http://www.ncbi.nlm.nih.gov/pubmed/?term=centdist'>CENTDIST</a><br>
3) Genome Profiling<br>
4) Overlap Analysis with ENCODE ChIP-seq data sets<br>
5) Histone Plot<br>
6) TSS Plot<br>
7) Peak Annotation to Genomic Regions<br>
8) Gene Annotation with <a href='http://www.ncbi.nlm.nih.gov/pubmed/?term=GREAT+improves+functional+interpretation+of+cis-regulatory+regions'>GREAT</a><br>
9) Repeat Analysis<br>
10) Conservation Plot<br>
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..and more to come!<br>

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Contact: zhizhuo@comp.nus.edu.sg
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Develop Team:
<br>
Zhang ZhiZhuo<br>
Pung SokeMay<br>
Yang RuiJie<br>
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